For summer-accumulation-type glaciers, the glaciological literature is lacking studies on determining the snow line altitude (SLA) from optical images at the end of the summer as an indicator of the equilibrium line altitude (ELA). This paper presents a workflow for extracting the SLA from Landsat images based on the variation in the albedo with the altitude in the central line area of glaciers. The correlation of >0.8 at the 99% confidence level between the retrieved SLAs with ELAs derived from the interpolation of ground-based, mass balance measurements indicated that the workflow can be applied to derive the SLA from end-of-summer satellite data as an indicator of ELA. The ELA was under-estimated by the calculated SLA. The relationship between the end-of-summer SLA and the ELA depends on the intensity of glacier melting. Subsequently, the workflow was applied to the seven glaciers in the Eastern Tien Shan Mountains, and a time series of the SLA was obtained using 12 end-of-summer Landsat scenes from 1994 to 2016. Over the whole study period, a mean SLA of 4011.6 ± 20.7 m above sea level (a.s.l.) was derived for the seven investigated glaciers, and an increasing SLA was demonstrated. The increase in SLAs was consistent for the seven glaciers from 1994 to 2016. Concerning the spatial variability, the east–west difference was prominent, and these differences exhibited a decreasing trend. The average SLA of each glacier is more influenced by its morpho-topographic variables. The interannual variations in the average SLA are mainly driven by the increasing summer air temperature, and the high correlation with the cumulative summer solid precipitation reflects the characteristics of the summer-accumulation-type glaciers.

Artificial glacier melt reduction is gaining increasing attention because of rapid glacier retreats and the projected acceleration of future mass losses. However, quantifying the effect of artificial melt reduction on glaciers in China has not been currently reported. Therefore, the case of Urumqi Glacier No.1 (eastern Tien Shan, China) is used to conduct a scientific evaluation of glacier cover efficiency for melt reduction between 24 June and 28 August 2021. By combining two high-resolution digital elevation models derived from terrestrial laser scanning and unmanned aerial vehicles, albedo, and meteorological data, glacier ablation mitigation under three different cover materials was assessed. The results revealed that up to 32% of mass loss was preserved in the protected areas compared with that of the unprotected areas. In contrast to the unprotected glacier surface, the nanofiber material reduced the glacier melt by up to 56%, which was significantly higher than that achieved by geotextiles (29%). This outcome could be attributed to the albedo of the materials and local climate factors. The nanofiber material showed higher albedo than the two geotextiles, dirty snow, clean ice, and dirty ice. Although clean snow had a higher albedo than the other materials, its impact on slowing glacier melt was minor due to the lower snowfall and relatively high air temperature after snowfall in the study area. This indicates that the efficiencies of nanofiber material and geotextiles can be beneficial in high-mountain areas. In general, the results of our study demonstrate that the high potential of glacier cover can help mitigate issues related to regions of higher glacier melt or lacking water resources, as well as tourist attractions.

The Mt.Tomur glaciers, in the Tian Shan mountains of Western China, are usually debris-covered, and due to climate change, glacial hazards are becoming more frequent in this region. However, no changes in the long-time series of glacier surface velocities have been observed in this region. Conducting field measurements in high-altitude mountains is relatively difficult, and consequently, the dynamics and driving factors are less studied. Here, image-correlation offset tracking using Landsat images was exploited to estimate the glacier surface velocity of glaciers in the Mt.Tomur region from 2000 to 2020 and to assess glacier ice thickness. The results show that the glacier surface velocity in the Mt.Tomur region showed a significant slowdown during 2000–2020, from 6.71 ± 0.66 m a⁻¹ to 3.95 ± 0.66 m a⁻¹, an overall decrease of 41.13%. The maximum glacier ice thickness in the Mt.Tomur region was estimated based on the ice flow principle being 171.27 ± 17.10 m, and the glacier average thickness is 50.00 ± 5.0 m. Glacier thickness at first increases with increasing altitude, showing more than 100 ± 10 m ice thickness between 3400 m and 4300 m, and then decreases with further increases in altitude. The reliability of the surface velocity and ice thickness obtained from remote sensing was proved using the measured surface velocity and ice thickness of Qingbingtan glacier No. 72 stall (the correlation coefficient R² > 0.85). The debris cover has an overall mitigating effect on the ablation and movement rate of Qingbingtan Glacier No. 72; however, it has an accelerating effect on the ablation and movement rate of glacier No. 74.

This work analyzed the spatial and temporal variations of the glaciers in the Ebi Lake basin during the period 1964 to 2019, based on the 1st and 2nd Chinese Glacier Inventories (CGI) and remote sensing data; this is believed to be the first long-term comprehensive remote sensing investigation on the glacier change in this area, and it also diagnosed the response of the glaciers to the warming climate by analyzing digital elevation modeling and meteorology. The results show that there are 988 glaciers in total in the basin, with a total area of 560 km² and average area of 0.57 km² for a single glacier. The area and number of the glaciers oriented north and northeast are 205 km² (327 glaciers) and 180 km² (265 glaciers), respectively. The glaciers are categorized into eight classes as per their area, which are less than 0.1, 0.1–0.5, 0.5–1.0, 1.0–2.0, 2.0–5.0, 5.0–10.0, 10.0–20.0, and greater than 20.0 km², respectively. The smaller glaciers between 0.1 km² and 10.0 km² account for 509 km² or 91% in total area, and, in particular, the glaciers smaller than 0.5 km² account for 74% in the total number. The glacial area is concentrated at 3500–4000 m in altitude (512 km² or 91.4% in total). The number of glaciers in the basin decreased by 10.5% or 116, and their area decreased by 263.29 km² (−4.79 km² a⁻¹) or 32% (−0.58% a⁻¹) from 1964 to 2019; the glaciers with an area between 2.0 km² and 5.0 km² decreased by the largest, −82.60 km² or −40.67% in the total area at −1.50 km² a⁻¹ or −0.74% a⁻¹), and the largest decrease in number (i.e., 126 glaciers) occurs between 0.1 km² and 0.5 km². The total ice storage in the basin decreased by 97.84–153.22 km³ from 1964 to 2019, equivalent to 88.06–137.90 km³ water (taking 0.9 g cm⁻³ as ice mass density). The temperature increase rate in the basin was +0.37 °C decade⁻¹, while the precipitation was +13.61 mm decade⁻¹ during the last fifty-five years. This analysis shows that the increase in precipitation in the basin was not sufficient to compensate the mass loss of glaciers caused by the warming during the same period. The increase in temperature was the dominant factor exceeding precipitation mass supply for ruling the retreat of the glaciers in the entire basin.

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world’s longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km² delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km² delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km²·a⁻¹ (0.96% a⁻¹ in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a⁻¹ in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a⁻¹), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a⁻¹) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years.

Glacier mass balance can be regarded as a major direct index of climate variations. In this paper, a geodetic method was used to evaluate the mass balance of Sawir glaciers based on topographic map DEM (Digital Elevation Model), SRTM 30 m DEM, ASTER 30 m DEM, and Sentinel-1 Synthetic Aperture Radar 10 m DEM between 1959–2021, in order to explore the response to climatic alterations. In the case of Muz Taw glacier, the first comprehensive dataset concerning mass-balance readings for the 2014–2021 period was provided based on the eight-year consecutive field measurements. The glaciological average mass balance reached –883.4 ± 130 mm a^–1 during this period. The geodetic mass balance for all glaciers of the Sawir Mountain range was −0.43 ± 0.12 m w. e. a⁻¹ between 1959 and 2000, and accelerated to −0.56 ± 0.13 m w. e. a⁻¹ between 2000 and 2021. A comparison of field measurements and remote-sensing approaches for determining the Muz Taw glacier’s mass balance between 2014–2021 proves the feasibility of the remote-sensing approach, which involves mass-balance monitoring based on DEMdata. In addition, our findings support the contention that air temperature is the dominant factor for accelerated glacier mass loss and surface elevation change.